To evaluate our novel algorithm, we use the F1-score. The F1-score is the harmonic average of the precision and recall and ranges between 0 and 1, with higher values being better. We evaluate the F1 score for each image of the test set of BSDS500[1]} at different thresholds for the edge prediction. We apply different thresholds since our results are edge probabilities with values between zero and one. The closest to 1 the edge value is, the more probable this edge is correct. Yet this metric does not provide a result for all the dataset. Hence similarly to papers [2]}, [3]}, [4]}, [5]} the Optimal Dataset Scale (ODS) and Optimal Image Scale (OIS) that provide a metric for the whole dataset.
